Pages that link to "Item:Q2102673"
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The following pages link to Physics-informed neural networks for shell structures (Q2102673):
Displaying 11 items.
- Mechanically aspirated radiation shields: a CFD and neural network design analysis (Q978242) (← links)
- Physics-informed multi-LSTM networks for metamodeling of nonlinear structures (Q2236167) (← links)
- A physics-guided neural network framework for elastic plates: comparison of governing equations-based and energy-based approaches (Q2237330) (← links)
- Physics-informed neural network for modelling the thermochemical curing process of composite-tool systems during manufacture (Q2237458) (← links)
- Geometric learning for computational mechanics. III: Physics-constrained response surface of geometrically nonlinear shells (Q6096461) (← links)
- A framework based on symbolic regression coupled with eXtended physics-informed neural networks for gray-box learning of equations of motion from data (Q6096490) (← links)
- Adversarial deep energy method for solving saddle point problems involving dielectric elastomers (Q6121800) (← links)
- Mesh reduction methods for thermoelasticity of laminated composite structures: study on the B-spline based state space finite element method and physics-informed neural networks (Q6540214) (← links)
- Gradient enhanced physics-informed neural network for iterative form-finding of tensile membrane structures by potential energy minimization (Q6558171) (← links)
- Phase-field modeling of fracture with physics-informed deep learning (Q6588261) (← links)
- Solving PDEs on spheres with physics-informed convolutional neural networks (Q6652574) (← links)
